RCAS (RNA Centric Annotation System) is an automated system that provides dynamic annotations for custom
input files that contain transcriptomic target regions. Such transcriptomic target regions could be, for instance, peak regions detected by
CLIP-Seq analysis that detect protein-RNA interactions, MeRIP-Seq analysis that detect RNA modifications (alias the epitranscriptome), or any
collection of target regions at the level of the transcriptome.
RCAS overlays the input target regions with the annotated protein-coding genes and calculates the Gene Ontology (GO) terms that may be enriched or
depleted in the input target regions compared to the background list of protein-coding genes. A Classical Fisher's Exact Test is applied for each GO term and the p-values
obtained for each GO term is corrected for multiple testing using both the False Discovery Rate and the Family-Wise Error Rate.
Similarly to the GO term enrichment analysis, RCAS also detects sets of genes as annotated in the Molecular Signatures
Database that are enriched or depleted in the queried target regions. Results are corrected for multiple-testing according to both the False Discovery Rate and the Family-Wise Error Rate.
MOTIF 1 MEME width = 8 sites = 517 llr = 2914 E-value = 4.1e-103
MOTIF 2 MEME width = 8 sites = 108 llr = 897 E-value = 7.0e-035
MOTIF 3 MEME width = 8 sites = 38 llr = 342 E-value = 1.9e+004
RCAS is developed by Dr. Altuna Akalin (head of the Scientific Bioinformatics Platform), Dr. Dilmurat Yusuf (Bioinformatics Scientist), and Dr. Bora Uyar (Bioinformatics Scientist) at the Berlin Institute of Medical Systems Biology (BIMSB) at the Max-Delbrueck-Center for Molecular Medicine (MDC) in Berlin.
RCAS is developed as a bioinformatics service as part of the RNA Bioinformatics Center, which is one of the eight centers of the German Network for Bioinformatics Infrastructure (de.NBI).